Clustering of obesity-related characteristics: A latent class analysis from the Canadian Longitudinal Study on Aging

Alessandra T. Andreacchi, Urun Erbas Oz, Carol Bassim, Lauren E. Griffith, Alexandra Mayhew, Marie Pigeyre, Saverio Stranges, Chris P. Verschoor, Laura N. Anderson*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Measures of obesity, including body mass index (BMI) and waist circumference (WC), do not fully capture the complexity of obesity-related health risks. This study identified distinct classes of obesity-related characteristics and evaluated their associations with BMI, WC, and percent body fat (%BF) using cross-sectional data from 30,096 participants aged 45–85 in the Canadian Longitudinal Study on Aging (2011–2015). Sixteen obesity-related variables, including behavioural, metabolic, physical health, and mental health/social factors, were included in a latent class analysis to identify distinct classes of participants. Adjusted odds ratios (OR) were estimated from logistic regression for associations between each class and obesity defined by BMI, WC and %BF. Six latent classes were identified: “low-risk” (39.8%), “cardiovascular risk” (19.4%), “metabolic risk” (16.9%), “sleep and mental health risk” (12.1%), “multiple and complex risk” (6.7%), and “cardiometabolic risk” (5.1%). Compared to “low-risk”, all classes had increased odds of BMI-, WC- and %BF-defined obesity. For example, the “complex and multiple risk” class was associated with obesity by BMI (OR: 10.70, 95% confidence interval (CI): 9.51, 12.04), WC (OR: 9.21, 95% CI: 8,15, 10,41) and %BF (OR: 7.54, 95% CI: 6.21, 9.16). Distinct classes of obesity-related characteristics were identified and were strongly associated with obesity defined by multiple measures.

Original languageEnglish
Article number106739
Pages (from-to)106739
JournalPreventive Medicine
Volume153
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Anthropometric measure
  • Canadian Longitudinal Study on Aging
  • Latent class analysis
  • Obesity
  • Older adults

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